Sun Kim

4.3k citations
181 papers · 2.9k · 1 hit paper · h-index 27

Impact in

    • MicroRNA in disease regulation
    • Cancer-related molecular mechanisms research
  • Neurology top 5%
    • Long-Term Effects of COVID-19

Papers in

    • Bioinformatics and Genomic Networks 36
    • Gene expression and cancer classification 25
    • RNA modifications and cancer 11
    • Machine Learning in Bioinformatics 11
    • Epigenetics and DNA Methylation 10
    • Ecology and Conservation Studies 7

Sun Kim

171 papers receiving 2.8k citations

Sun Kim's Hit Papers

SARS-CoV-2 and Stroke in a New York Healthcare System 2020 · 452 citations
4520+2+4Years since publication100200300400

Peers

Sun Kim
Comparison fields: 5 of 151
  • Cancer Research 378
  • Neurology 347
  • Molecular Biology 1.3k
  • Infectious Diseases 244
  • Computational Theory and Mathematics 216
Replace Philipp E. Geyer with:
Philipp E. Geyer Germany
Yunping Zhu China
Davood Bashash Iran
Farrokh Mehryary Finland
Mikaela Koutrouli Denmark
Hua Su China
Hsueh‐Fen Juan Taiwan
Markus List Germany
Mickaël Guedj France
Sune Pletscher-Frankild Denmark
Sun Kim relative to Philipp E. Geyer Germany Philipp E. Geyer's profile →
Citations per field
00.5×6.2×
Philipp E. Geyer · 1×
Citations per year

Countries citing papers authored by Sun Kim

Since Specialization
Citations

This map shows the geographic impact of Sun Kim's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Sun Kim with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sun Kim more than expected).

Fields of papers citing papers by Sun Kim

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sun Kim. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Sun Kim. The network helps show where Sun Kim may publish in the future.

Co-authors

The 25 scholars most cited alongside Sun Kim, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Sun Kim Line = papers co-authored together Sun Kim links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 181 papers — load more, or switch the sort, to bring in the rest.

#Work
1
SARS-CoV-2 and Stroke in a New York Healthcare System
Hit paper breakdown →
2020452
2 2009143
3 2011122
4 2008102
5 201895
6 202187
7 202369
8 201968
9 202267
10 201347
11 201745
12 201641
13 201441
14 201539
15 202038
16 201338
17 201437
18 202036
19 201936
20 202034

About Sun Kim

Sun Kim is a scholar working on Molecular Biology, Plant Science, Cancer Research, Computational Theory and Mathematics and Ecology, Evolution, Behavior and Systematics, having authored 181 papers that have together received 2.9k indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (36 papers), Gene expression and cancer classification (25 papers), Computational Drug Discovery Methods (14 papers), Agriculture, Soil, Plant Science (13 papers), RNA modifications and cancer (11 papers), Machine Learning in Bioinformatics (11 papers), Epigenetics and DNA Methylation (10 papers) and Ecology and Conservation Studies (7 papers). The work is most often cited by research in Cancer Research (378 citations), Neurology (347 citations), Molecular Biology (1.3k citations), Infectious Diseases (244 citations) and Computational Theory and Mathematics (216 citations) Sun Kim has collaborated with scholars based in South Korea, United States and Puerto Rico. Frequent co-authors include Sangseon Lee, Sangsoo Lim, Heejoon Chae, Youngjun Park, Inuk Jung, Kyuri Jo, Seungyoon Nam, Minsik Oh, Kwangmin Choi and Seokjun Seo. Their work appears in journals such as Bioinformatics, Scientific Reports, Briefings in Bioinformatics, Synlett and BMC Bioinformatics.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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